Which of These Statements is True of Big Data?
Which of the following statements is true of big data? “Big data” and “big data analytics” would be the two most apt answers. The reason is simple: big data is now a part of everyday life for people from all walks of life, not just financial industry professionals. It is not something that only exists in the realm of finance.
In this technological age, information is not only plentiful, it is also accessible in a variety of formats. One can easily collect data sets from the Internet, satellite images from space, and even analyze them to generate statistical comparisons of historical data sets. Thus, the term “big data” is not so much an exaggeration as a fundamental truth. Today’s generation of mobile devices running on various operating systems such as Android and iPhones is proof of this. And what a brilliant way to bring up the entire subject with a single concept: analytical thinking.
Big data analytics is the scientific process of extracting, processing, and storing large sets of data from varied sources. Today’s data sets are complex, requiring sophisticated methods of analysis and visualization. As a consequence, analytical processes usually involve more than just computing power. They also involve several people working simultaneously in an integrated team, each contributing his or her individual contribution according to his or her expertise.
Data sets are analyzed using various techniques. In order to describe a set, one may use a mathematical expression like “x = (y + archiere)”. Mathematical “theorems” are used to identify relationships among variables and the other variables. A mathematical “algebra” is a branch of mathematics that is concerned with interpreting symbols and numbers so as to derive an equation, or more specifically, a geometric figure. These different techniques and concepts that compose big data analytics have different perspectives and uses, but all of them ultimately lead to one basic concept.
“The big data is bigger than the data that is measured” – Algorithms controlling the processing power of computers. Computers are able to process large amounts of data. In turn, these massive amounts of data are stored in huge networks. Large databases, obtained through big data analytics, are used to support business decisions made by management. Management thus learns which of its customers have sales records and which have new orders; it learns which of its products are selling best and which are not.
“Big data is unpredictable” – The unpredictability of statistics generated by computers cannot be ruled out. Computers will make mistakes. Human error will also be unavoidable in certain cases. However, thanks to the exponentially growing storage capabilities of computers and their increasingly complex networks, the probability of human error is next to zero.
“A business cannot predict which of the following statements is true of big data?” – Data is always unpredictable. If the right process is not followed, a lot can go wrong. For instance, an online store may lose a lot of sales due to a system error. But this could also be an opportunity for the business to increase its sales.
“Big data analytics is costly” – This one may seem to be a bit of an exaggeration. However, companies spending money on big data analytics are assured of great results in terms of profit. Most of the big data analytics solutions are actually sold at a low cost. Therefore, business owners should not worry about spending too much money on this aspect.
“Businesses should not rely on data analytics” – Again, this is a fairly facile answer to the question, which of the following statements is true of big data? Most businesses, however, do not heed this advice. As a result, businesses end up wasting a lot of resources, and even end up making losses. The most important point to remember here is that a business needs to think smart, not hard, when it comes to using big data analytics.
“Data is messy” – This is another one of those blunt but nevertheless true statements, which of the following statements is true of big data? Firstly, data analysis needs the integration of huge amounts of unstructured or semi-structured data. Secondly, data analysis itself is also a very tedious and time-consuming process. Therefore, big data analytics systems are designed so that data is cleaned up intelligently at the same time as it is used in decision making.
Indeed, many of the so-called myths concerning big data are based on misleading premises. Businesses need to be very cautious about what they say, especially if they want to use big data in their business. By educating themselves about the truth of these statements, and by choosing vendors who offer solutions that actually work, businesses will save a lot of time, money, and ultimately find themselves much more successful than they ever thought possible.